Information
- Publication Type: Bachelor Thesis
- Workgroup(s)/Project(s):
- Date: March 2017
- Date (Start): 1. October 2016
- Date (End): 8. March 2017
- Matrikelnummer: 1226809
- First Supervisor: Eduard Gröller
Abstract
This thesis describes a technique for editing segmentation results of vessels, which should enhance usage and reduce work duration for physicians by using a simple and fast way of interaction. Moreover also a quick calculation of an accurate result was of primary interest. Since vascular structures are vulnerable to diseases, vessels are the main focus of this thesis. Nowadays, Image Analysis is able to facilitate the medical diagnosis procedure. Since stroke treatment is time-crucial, appropriate algorithms should be fast and enable an accurate depiction of the arteries to simplify the diagnostic process. However, because automatic segmentation is often quite inaccurate and manual segmentation is tedious, neither of these two methods alone is often adequate for usage. Because of this we suggest to combine the fast automatic segmentation and the exact manual editing done by clinical experts. To reduce effort and working time of the medical staff, this thesis describes different techniques, which were developed to modify and, more importantly, to improve the segmentation results. The segmentation mask can be altered as its components can be separately removed and independent elements can be connected. A framework was implemented, with which a user is able to perform these tasks interactively. The deletion process is supported by various metrics, which enable the search and removal of similar structures. Also this framework assists the reconnection of vessels by finding the most likely connection by the means of image intensities and their gradients. The main goal of this thesis was to facilitate and accelerate the editing process by implementing fast semi-automatic algorithms. Intuitive interaction methods also had a major impact on the design.Additional Files and Images
Weblinks
No further information available.BibTeX
@bachelorsthesis{Heim-2017,
title = "Semiautomated Editing of Vessel Segmentation Masks",
author = "Anja Heim",
year = "2017",
abstract = "This thesis describes a technique for editing segmentation
results of vessels, which should enhance usage and reduce
work duration for physicians by using a simple and fast way
of interaction. Moreover also a quick calculation of an
accurate result was of primary interest. Since vascular
structures are vulnerable to diseases, vessels are the main
focus of this thesis. Nowadays, Image Analysis is able to
facilitate the medical diagnosis procedure. Since stroke
treatment is time-crucial, appropriate algorithms should be
fast and enable an accurate depiction of the arteries to
simplify the diagnostic process. However, because automatic
segmentation is often quite inaccurate and manual
segmentation is tedious, neither of these two methods alone
is often adequate for usage. Because of this we suggest to
combine the fast automatic segmentation and the exact manual
editing done by clinical experts. To reduce effort and
working time of the medical staff, this thesis describes
different techniques, which were developed to modify and,
more importantly, to improve the segmentation results. The
segmentation mask can be altered as its components can be
separately removed and independent elements can be
connected. A framework was implemented, with which a user is
able to perform these tasks interactively. The deletion
process is supported by various metrics, which enable the
search and removal of similar structures. Also this
framework assists the reconnection of vessels by finding the
most likely connection by the means of image intensities and
their gradients. The main goal of this thesis was to
facilitate and accelerate the editing process by
implementing fast semi-automatic algorithms. Intuitive
interaction methods also had a major impact on the design.",
month = mar,
address = "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria",
school = "Institute of Computer Graphics and Algorithms, Vienna
University of Technology ",
URL = "https://www.cg.tuwien.ac.at/research/publications/2017/Heim-2017/",
}